My post on Bizible’s new local search ranking factors study is now up at SearchEngineLand. You can also get more detail on the study and the results on Bizible’s blog. As mentioned in my SEL post, Bizible claims the study is scientifically valid and while in general I liked their approach, I can think of a number of flaws in the methodology – the #1 flaw being that they are not Google And of course CORRELATION DOES NOT EQUAL CAUSATION. I expect the data and methodology to generate a fair amount of discussion.
Here’s the list of the top factors according to the study. They are broken down between factors that affected listings in blended results v those in “pure local” results.
Factors in Integrated/Blended Results
For those pages in the integrated results, the top local ranking factors while holding all other variables constant are:
- Primary category matches a broader category of the search category = 1.42 improvement in rank. For example, primary category is set to “restaurant” and the search category was “pizza.”
- The search category or a synonym in the business name = 0.64 improvement in rank.
- The search category or a synonym in “at a glance” = 0.36 improvement in rank.
- Five or more Google reviews = 0.31 improvement in rank.
- At least one photo = 0.25 improvement in rank.Listings with all of these signals showed an improvement in ranking of about three positions – pretty high considering that on average there were five integrated local results in the main search page.
Factors in Pure Local Results
For those pages not in the integrated results, the top local ranking factors while holding all other variables constant are:
- Five or more Google reviews = 1.47 improvement in rank.
- Search city in “at a glance” = 1.42 improvement in rank.
- Search category or a synonym in in review content = 0.97 improvement in rank.
- Search category or a synonym in the business description = 0.85 improvement in rank.
- Search category or a synonym in “at a glance” = 0.85 improvement in rank.
- Primary category matches the search category = 0.79 improvement in rank.
- Search category or a synonym in the business name = 0.75 improvement in rank.
- Secondary business category that was a broader category than the search category = 0.68 improvement in rank.( i.e. secondary category is “restaurant” when searching for “Seattle pizza.”)
- At least one photo = 0.66 improvement in rank.
- Owner verified listing = 0.52 improvement in rank.Listings with all of these signals showed an improvement in ranking of about nine positions. Given that they were in the top 30, an improvement of nine is significant.
While this is all juicy stuff, I really liked their “Surprising Takeaways” section:
- Having a physical address in the city of the search did not turn out to be a strong ranking factor, only distance from centroid seemed to matter. So, if you are just outside the city and your address is not officially in the city, this didn’t seem to hurt any more than a business whose address was in the city, but just as far from the centroid.
- Not having any Google reviews or having an average review score of one hurt ranking, although the incremental increase in ranking as the review score increased from two through five was negligible.
- The presence of a business description alone did not help ranking, but having the search category in the business description did help.
- Getting your fifth Google review significantly helped ranking, although incremental reviews between one and four and above five had a very small impact on ranking. You have to get 100+ reviews to again have a significant impact on ranking.
- On average, for every mile away from the centroid, ranking dropped by 0.4 of a position. Note that this is the average across all 22 cities. In very dense cities like New York, this number was higher and in sprawling cities it was lower.
- Seven of the 484 queries did not have local results on the main page (they removed those 7 from their analysis). On average, there were five local results on the main page.
To see the list of factors they measured, more on their methodology, etc. definitely check out their post.
And since you asked, no, I have no affiliation with these guys other than they gave me a preview of the data and I thought it was interesting. Let the snarky comments commence…